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Optimum socio-environmental flows approach for reservoir operation strategy using many-objectives evolutionary optimization algorithm

机译:利用多目标进化优化算法,最佳的社会环境流方法储层运行策略

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Water resource system complexity, high-dimension modelling difficulty and computational efficiency challenges often limit decision makers' strategies to combine environmental flow objectives (e.g. water quality, ecosystem) with social flow objectives (e.g. hydropower, water supply and agriculture). Hence, a novel Optimum Social-Environmental Flows (OSEF) with Auto-Adaptive Constraints (AAC) approach introduced as a river basin management decision support tool. The OSEF-AAC approach integrates Socio-Environmental (SE) objectives with convergence booster support to soften any computational challenges. Nine SE objectives and 396 decision variables modelled for Iraq's Diyala river basin. The approach's effectiveness evaluated using two non-environmental models and two inflows' scenarios. The advantage of OSEF-AAC approved, and other decision support alternatives highlighted that could enhance river basin SE sectors' revenues, as river basin economic benefits will improve as well. However, advanced land use and water exploitation policy would need adoption to secure the basin's SE sectors. (C) 2018 Elsevier B.V. All rights reserved.
机译:水资源系统复杂性,高维建模难度和计算效率挑战通常限制决策者与社会流动目标相结合环境流动目标(例如水质,生态系统)(例如水电,供水和农业)。因此,具有自适应约束(AAC)方法的新型最佳社会环境流(OSEF)作为河流盆管理决策支持工具。 OSF-AAC方法将社会环境(SE)的目标与融合助推器支持集成,以软化任何计算挑战。为伊拉克Diyala River盆地建模的九种目标和396个决策变量。该方法的有效性使用两个非环境模型和两个流入的情景进行了评估。 OSEF-AAC批准的优势以及突出的其他决策支持替代方案可以增强流域SE部门的收入,因为流域经济效益也会有所改善。但是,先进的土地利用和水开采政策需要采用来保护盆地的SE部门。 (c)2018年elestvier b.v.保留所有权利。

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